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Putra Wanda
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ijicom@respati.ac.id
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Department of Informatics, University of Respati Yogyakarta
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INDONESIA
International Journal of Informatics and Computation
Published by Universitas Respati Yogyakarta
ISSN : 26858711     EISSN : 27145263     DOI : 10.35842/ijicom
Core Subject : Science,
Computer Science & IT
International Journal of Informatics and Computation (IJICOM) is an international, peer-reviewed, open-access journal, that publishes original theoretical and empirical work on the science of informatics and its application in multiple fields. Our concept of Informatics includes technologies of information and communication as well as the social, linguistic, and cultural changes that initiate, accompany, and complicate their development. IJICOM aims to be an international platform to exchange novel research results in simulation-based science across all scientific disciplines. It publishes advanced innovative, interdisciplinary research where complex multi-scale, multi-domain problems in science and engineering are solved, integrating sophisticated numerical methods, computation, data, networks, and novel devices. The scope of this journal includes IoT, 5G, Artificial Intelligence, sensor networks, and high-resolution imaging techniques. This new discipline in science combines computational thinking, modern computational methods, devices, and collateral technologies to address problems far beyond the scope of traditional numerical methods
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 61 Documents
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Pooling Comparison in CNN Architecture for Javanese Script Classification Mujastia Feliati Muhdalifah
International Journal of Informatics and Computation Vol 3 No 2 (2021): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v3i2.30

Abstract

Javanese script is evidence of the past culture, which contains various current language learning, including script recognition. However, learning traditional scripts becomes less attractive to the students. Thus, we propose a learning method to enable character recognition among students to deal with the issues. We offer a novel CNN architecture and compare different pooling layers for Javanese script classification. We calculate the separate pooling layer to reduce extensive feature extraction of the image. We present the model comparison results in Javanese character classification to convince our development.
Modern Privacy-Preserving and Security Schemes in Social Networks: A Review Putra Wanda
International Journal of Informatics and Computation Vol 3 No 2 (2021): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v3i2.39

Abstract

Online Social Network (OSN) is a popular application to exchange messages over the internet. However, millions of users are still under threat because of protection drawbacks. Many papers have proposed security methods, including firewalls, protocols, cryptography, statistical analysis, even learning algorithms. This paper provides an overview of privacy and security issues and describes multiple OSN protection techniques. We present various security schemes in OSNs and outline existing solutions to mitigate those attacks. This paper also discusses future research directions regarding OSN security problems and techniques.
DeepSkin: Robust Skin Cancer Classification Using Convolutional Neural Network Algorithm Marselina Endah H.
International Journal of Informatics and Computation Vol 3 No 2 (2021): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v3i2.40

Abstract

Classification of skin cancer is a growing research topic with significant challenges in the image processing. Learning algorithms for classifying a kind of skin cancer have been presented in recent articles to accelerate the diagnosis process with a rapid and accurate diagnosis. However, effective detection of skin cancer requires extensive graphical data. Inspired by deep learning successful results in computer vision, A Convolutional Neural Network (CNN) is proposed in this study to build a skin cancer classification model. We conduct this experiment by collecting massive skin cancer datasets, conducting pre-processing, training models, and evaluating the performance. Based on the experiment result, the benign and malignant classification model can obtain a good accuracy with a slight loss. Therefore, the results obtained reached an accuracy of 54%.
Implementation of KNN Algorithm for Occupancy Classification of Rehabilitation Houses Nurhadi Wijaya; Joko Aryanto; Kasmawaru Kasmawaru; Anang Faktchur Rachman
International Journal of Informatics and Computation Vol. 4 No. 2 (2022): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v4i2.36

Abstract

The 2010 eruption of Mount Merapi and the resulting rain lava in Central Java's Kab. Sleman DIY and Magelang Regency damaged homes and infrastructure. According to the Head of BNPB Regulation No. 5, the Community Rehabilitation and Reconstruction and Community-Based Settlement program plan is utilized to repair and rebuild properties damaged by the 2011 Merapi eruption. Two thousand five hundred sixteen residences that will stay in the area have been built permanently due to this initiative. Occupancy rates (permanent occupancy) are used by the World Bank's Key Performance Indicators (KPI) to gauge a program's effectiveness. The database has information on how the software was used and proved successful. Databases, essential tools for introducing new data patterns and revealing previously hidden information, are used in data mining. This study applies the KNN algorithm to classify the house's occupancy status data after Mount Merapi's eruption. The accuracy results obtained from the classification of 82.03%, and the performance of the results through the AUC obtained a value of 0.935.
Implementation of Deep Learning for Classification of Mushroom Using CNN Algorithm Imam Mahfudz I'tisyam; Nurhadi Wijaya; Rike Pradila
International Journal of Informatics and Computation Vol. 5 No. 1 (2023): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v5i1.42

Abstract

Mushrooms are a type of low-level plant that lacks chlorophyll. One of the advantages of fungi is that they are commonly utilized as food items in the community. This paper discussed the implementation of CNN for the classification of mushrooms. The project aims to develop a robust system that can automate the labor-intensive task of mushroom classification. The CNN model will be trained on a large dataset of annotated mushroom images, learning to extract meaningful features and patterns for accurate categorization. To evaluate the performance of the developed system, a comprehensive set of metrics, including accuracy, precision, recall, and F1 score, will be used. The dataset will be split into training, validation, and testing sets to assess the model's generalization ability to unseen data. Based on the experimental result, the average accuracy rate in the Agaricus Portobello test was % -99.89 %, % -99.89 % in the Amanita Phalloides test, % -99.59 % in the Cantharellus Cibarius test, % -98.89 % in the Gyromitra Esculenta test, % -99.96 % in the Hygrocybe Conica, and % -99.93 % in the Omphalotus Orealius.
ConFruit: Effective Fruit Classification Using CNN Algorithm Rani Laple Satria; M Hizbul Wathan
International Journal of Informatics and Computation Vol. 5 No. 1 (2023): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v5i1.44

Abstract

Fruit is one type of food containing nutrients, vitamins, and minerals that are generally very good for daily consumption. However, various fruit choices make consumers confused about choosing and buying fruit. Many papers have proposed fruit classification to deal with this problem in recent years. Therefore, this study offers a new recommendation model using type to dissect fruit so that buyers can more easily recognize fruit. We collected the primary dataset from Cagle to 3000 fruit images. Based on experiments, our research achieved good accuracy results using the CNN algorithm to classify fruit so that consumers can distinguish between types of fruit. Experimentally demonstrated, we harvested the promised results with better accuracy and small losses than the general fruit classification study.
Effective Stock Prediction Model Using MACD Method Hamzah; Sugeng Winardi
International Journal of Informatics and Computation Vol. 4 No. 2 (2022): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v4i2.51

Abstract

Stock market predictions help investors to optimize benefits in the financial markets. Various papers have proposed different techniques in stock market forecasting, but no model can provide accurate predictions. In this study, we discuss how to predict stock prices using a MACD (Moving Average Convergence/Divergence Oscillator) method. We collect the dataset, preprocess it, extract features, evaluate the model, and then deploy the MACD method to develop a stock price prediction model. In this study, we collect several features, including date, open, high, low, close, and volume, to conduct the training and testing process. The results of the experiments reveal good accuracy and a low error rate. As a result, it has the potential to be a promising solution for dealing with accurate and dynamic prices. Based on the experimental result, our proposed model can obtain a transaction profit rate of 40.00% and an average profit per transaction of 1.42%.
SIMANTUL: Model of Internal Quality Audit Management System in Higher Education Sri Hasta Mulyani; Ariyanto Nugroho; Maisarah Nurain
International Journal of Informatics and Computation Vol. 4 No. 2 (2022): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v4i2.52

Abstract

Many organizations carry out the quality assurance system through the Internal Quality Assurance System (SPMI) and the External Quality Assurance System (SPME). The SPMI framework uses the stages of a continuous quality assurance cycle with the PPEPP method (Application, Implementation, Evaluation, Control, and Improvement), which is carried out periodically to achieve University's Vision, Mission, Goals, and Targets. This paper discusses the implementation stages of the internal quality audit management system at Universitas Respati Yogyakarta, Indonesia. Using an information system, the university audit body, BPM, regularly and consistently carries out an Internal Quality Audit (AMI) every year to audit the implementation of academic and non-academic activities at the University. In this research, we construct an audit system, namely the E-Audit application, with the Waterfall software development method. This study can produce an efficient system called SIMANTUL, which refers to the Higher Education Accreditation assessment instrument version 3.0 and can store documents digitally.
How to Stepping up Characters Recognition using CNN Algorithm? Al-Sadi Khaled; Putra Wanda
International Journal of Informatics and Computation Vol. 4 No. 2 (2022): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v4i2.53

Abstract

Character recognition is very important to understand ancient culture. Various papers proposed numerous to deal with handwritten character recognition. However, several traditional remain drawbacks because methods still rely on operations based on visual capabilities. Therefore, to deal with the issue, we propose a novel recognition model using a Convolutional Neural Network to produce an effective result. To build the model, we collect datasets, do preprocessing, training with several different parameters to get the highest accuracy results. Based on experiments, our proposed model can produce an accuracy quality with a value of 98.00%.
Production Cost Control using Activity-Based Costing Methods in Information Systems Suparto Darudiato; Yunus Widjaja
International Journal of Informatics and Computation Vol. 4 No. 2 (2022): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v4i2.54

Abstract

Companies engaged in furniture manufacturing with marketing targets mostly abroad are faced with very tight price and quality competition that requires a more accurate production costing system than traditional methods, which are still widely used in Indonesia. In general, companies use cost calculation methods that pay attention to only one cost driver, resulting in deviations in the calculation of actual production costs. A production cost calculation method is proposed using activity-based costing to overcome this problem. Many companies have used this method in developed countries, showing improvements in calculating production costs. The activity-based calculation method takes into account the activities that are cost drivers and is taken into account in obtaining actual production costs. So that the cost planning for the management is better, in this study, calculations using traditional methods are shown, and the results are compared with the results of the activity-based costing (ABC) method. Then an analysis of the system needed for applying the information system-based ABC method and the proposed implementation is also carried out. The information system will help calculate costs faster and more accurately.

Page 3 of 7 | Total Record : 61

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